Access to this full-text is provided by Springer Nature.
Content available from BMC Psychiatry
This content is subject to copyright. Terms and conditions apply.
R E S E A R C H A R T I C L E Open Access
Psychological distress associated with the
COVID-19 pandemic and suppression
measures during the first wave in Belgium
Vincent Lorant
1*
, Pierre Smith
1
, Kris Van den Broeck
2
and Pablo Nicaise
1
Abstract
Background: The COVID-19 pandemic and subsequent suppression measures have had health and social
implications for billions of individuals. The aim of this paper is to investigate the risk of psychological distress
associated with the COVID-19 pandemic and suppression measures during the early days of the lockdown. We
compared the level of psychological distress at the beginning of that period with a pre-pandemic health survey
and assessed the psychological effects of exposure to the COVID-19 pandemic and changes in social activity and
support.
Methods: An online survey was distributed to the general population in Belgium 3 days after the beginning of the
lockdown. 20,792 respondents participated. The psychological distress of the population was measured using the
GHQ-12 scale. Social activities and support were assessed using the Social Participation Measure, the Short
Loneliness Scale, and the Oslo Social Support Scale. An index of subjective exposure to the COVID-19 pandemic
was constructed, as well as a measure of change in occupational status. Measurements were compared to a
representative sample of individuals extracted from the Belgian Health Interview Survey of 2018. Bootstrapping was
performed and analyses were reweighted to match the Belgian population in order to control for survey selection
bias.
Results: Half of the respondents reported psychological distress in the early days of the lockdown. A longer period
of confinement was associated with higher risk of distress. Women and younger age groups were more at risk than
men and older age groups, as were respondents who had been exposed to COVID-19. Changes in occupational
status and a decrease in social activity and support also increased the risk of psychological distress. Comparing the
results with those of the 2018 Belgian Health Interview shows that the early period of the lockdown corresponded
to a 2.3-fold increase in psychological distress (95% CI: 2.16–2.45).
Conclusions: Psychological distress is associated with the consequences of the COVID-19 pandemic and
suppression measures. The association is measurable from the very earliest days of confinement and it affected
specific at-risk groups. Authorities should consider ways of limiting the effect of confinement on the mental and
social health of the population and developing strategies to mitigate the adverse consequences of suppression
measures.
© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
changes were made. The images or other third party material in this article are included in the article's Creative Commons
licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons
licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the
data made available in this article, unless otherwise stated in a credit line to the data.
* Correspondence: vincent.lorant@uclouvain.be
1
Institute of Health and Society (IRSS), Université Catholique de Louvain,
Brussels, Belgium
Full list of author information is available at the end of the article
Lorant et al. BMC Psychiatry (2021) 21:112
https://doi.org/10.1186/s12888-021-03109-1
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
In 2020, the outbreak and spread of COVID-19 led
many governments around the world to adopt suppres-
sion measures, including lockdowns, bans on public
events, and social distancing. Such measures, although
effective in containing the spread of the virus [1], may
have had unintended consequences for the mental health
of the population. Brooks and colleagues performed a
rapid review of the literature on the psychological im-
pact of quarantine in previous viral outbreaks and re-
ported several negative psychological outcomes [2].
Three main pathways were involved. First, continuous
reports of information about outbreaks in the press and
social media were likely to increase stress, anxiety, and
fear of the disease and its consequences among the
population. The confinement period due to COVID-19
occurred in the context of an unprecedented pandemic,
a crisis affecting the entire world [3]. Anxiety may have
been further increased by the dissemination of verified
and unverified information about the consequences and
spread of the outbreak [4–6]. Anxiety and stress were
likely to be even greater among those affected by the dis-
ease at home, those at risk of being affected, and those
who had a relative or a close friend outside the home
who was affected [3].
Second, the suppression measures deliberately led to
a reduction in social contact, social activity, and social
support, dramatically changing the social lives of indi-
viduals. Limiting social contact affects negatively the
mental health of the general population, as evidenced
in previous studies [7,8]. Such limitations have various
possible consequences; confinement is likely to increase
feelings of stress among individuals by limiting both ac-
cess to public and open spaces and contact with people
outside the home [9,10]. Confinement also lead to
greater social exclusion, loneliness, reduced social sup-
port, and an increase in alcohol and substance use, all
of which are key risk factors for poor mental health and
suicidal behaviour [11–15].
Third, the spread of COVID-19 and suppression mea-
sures may increase stress by affecting labour conditions
[16]. The workload of some, who were not employed in
essential sectors, decreased, while the workload of
others, such as health care professionals, increased [17,
18]. There was also an increase in teleworking for many
people employed in services [19]. The closure of schools
also led to children being stuck at home with their
parents. Children were particularly vulnerable to
confinement [20], while parents had to combine the
management of their professional activities with coping
with children at home [21,22]. Many people also feared
possible long-term consequences of the reduction in
activity, particularly for employment and for their
income [23].
Finally, the COVID-19 outbreak and subsequent policy
measures may not affect all sociodemographic groups in
the same way. They were likely to affect the social and
mental health of some groups of the population which
are more vulnerable to the three pathways mentioned
above, including women [7,24] and people who were
already physically, mentally, or socially vulnerable prior
to the outbreak [25–27]. The main aim of this paper,
therefore, was to investigate the risk of psychological
distress that may be associated with the COVID-19
pandemic and subsequent confinement measures, par-
ticularly during the early days of confinement, in order
to measure the short-term effects of the pandemic and
the subsequent measures. In light of the previous results
reported in the literature, three main research questions
were addressed: (a) How did the level of psychological
distress at the start of the lockdown period compare
with the level of psychological distress usually measured
in the general population? (b) Which health, social, and
economic conditions predicted psychological distress at
the beginning of the confinement period? (c) Was the
risk of psychological distress associated with the dur-
ation of the lockdown?
Our study complements previous studies in several
ways: we compare our results to a dataset from a pre-
COVID19 national survey, helping to shed light on the
changes, at populational level, associated with the pan-
demic and the accompanying measures. We also attempt
to disentangle the different pathways involved and we
compare the level of different symptoms in a pre-
COVID19 period with the level of symptoms at the
beginning of the lockdown. Finally, Belgium is an inter-
esting case study as it has been among the countries
worst hit by the COVID-19 pandemic (see below).
Methods
Setting
Belgium has been hit badly by the COVID-19 pandemic.
The epidemiological outcomes have been poor: it has
one of the highest numbers of deaths per inhabitant and
the situation in nursing homes is critical [28]. It was one
of the first European countries to implement suppres-
sion and nation-wide lockdown measures, including the
closure of all schools and higher education institutions.
Later, Belgium also pioneered limiting the size of the
household social bubble.
Design and data
We carried out an online survey of the general popula-
tion in Belgium. This survey design strategy was chosen
because movement of the population was restricted and
we wanted to quickly evaluate the risk of psychological
distress at the very beginning of the lockdown. The sur-
vey was widely publicised and disseminated through
Lorant et al. BMC Psychiatry (2021) 21:112 Page 2 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
social media and the main national newspapers and was
advertised on the radio and on TV. In Belgium, lock-
down measures were implemented from 18 March 2020.
The survey was open from 20 March to 9 April 2020.
During that period, 27,857 individuals clicked on the
web survey and 21,734 agreed to complete it. After ex-
cluding responses with missing data, we were left with
20,792 valid responses. The survey was designed to allow
comparison with the level of psychological distress found
in the Belgian population under normal conditions. To
that end, we obtained the most recent such survey, the
Belgian Health Interview Survey of 2018 (n= 7793),
hereafter BE.HIS2018 [29,30]. This survey, which has
been carried out every 4–5 years since 1997, assesses the
health status of the population and its social and behav-
ioural determinants, using a representative sample from
each of the three Belgian Regions (Flanders, Wallonia,
and Brussels).
Measures
The scales were selected with particular emphasis on
validated, short, and population-level scales that had
been used in other health surveys, including the pre-
COVID-19 BE.HIS, and were already translated and
validated in French, Dutch, and English. The primary
outcome, psychological distress, was measured with the
GHQ-12 as in the BE.HIS. GHQ-12 is a 12-item scale of
common mental disorders [31] that displays good
psychometric properties, with a Chronbach’s alpha score
of 0.90 on the Likert scale [32,33]. We used the GHQ
scoring method, which returns a continuous score ran-
ging from 0 to 12, with a score of 4 or more indicating
the likelihood of a mental disorder [33].
We explored health, social, and occupational risk fac-
tors. Health risk factors were related to the direct or in-
direct exposure of the population to the COVID-19
outbreak and to subjection to the subsequent lockdown
measures. Exposure was assessed using an index that
was constructed on the basis of eight dichotomous (yes/
no) questions about proven (tested or diagnosed) or sus-
pected COVID-19 infection of the respondent and/or of
someone living with the respondent and/or of a relative
or acquaintance. The COVID-19 exposure index ranged
from 0 (low exposure) to 8 (high exposure). We also cal-
culated the length of time for which respondents had
been subjected to the lockdown measures, using the
number of days between 18 March 2020 and the day of
completion of the questionnaire.
Social risk factors were related to social activity and
support. The volume of social activity was assessed using
an adaptation of the Social Participation Measure (SPM),
an adaptation that was developed as part of the Com-
mon Cold Project [34]. Respondents were asked about
the frequency of six types of social activity during a
normal week, before and after the start of the lockdown
period. The score for change in social activity between a
normal week and the first week of the lockdown period
ranged from −18 (considerable increase in activity) to
18 (considerable decrease in activity). Social support was
assessed using the 3-item Oslo Social Support Scale,
which returns a score ranging from 3 (poor social sup-
port) to 14 (strong social support). The social support
scores were categorised into three groups (3 to 8: weak;
9 to 11: moderate; 12 to 14: strong social support) [35].
Social isolation was measured using the Short Loneliness
Scale (LON), ranging from 3 (low level of loneliness) to
12 (high level of loneliness) [36].
Occupational risk factors were related to changes in
occupational status, workload, and income. Respondents
were asked whether they had experienced changes in
their income, employment status, and/or working condi-
tions (such as increased teleworking) following the
COVID-19 outbreak and lockdown measures. Finally,
socio-demographics (age, gender, occupational status,
and educational status) and items allowing the identifi-
cation of specific vulnerable subgroups (household com-
position, profession, and previous history of long-term
illness) were also requested and included as control vari-
ables. The full questionnaire is available online in
French, Dutch, and English (www.uclouvain.be/
covidandI).
Ethical review
Belgian Law does not require approval by an ethics com-
mittee for an online survey of the general population.
The study is, however covered by privacy regulations.
Participants were provided with all legal information re-
lating to consent. All information related to respondents’
consent and the GDPR is available on request.
Statistical analysis
The statistical analysis was a three-step process. First, we
computed the level of psychological distress by age and
gender group. Then, we performed linear and logistic re-
gressions in order to examine the association between
psychological distress and the independent covarites (ex-
posure to COVID-19, lockdown measures, social and
labour conditions), controlling for socio-demographic
characteristics and the existence of a previous long-term
illness. Finally, we assessed the risk of psychological dis-
tress associated with COVID-19 and subsequent lock-
down measures by comparing the ratios found in our
sample with those found in a pre-COVID-19 bench-
mark, the BE.HIS2018 sample. As the composition of
the two samples differed, the rate of psychological dis-
tress in the two samples was calculated conditioning for
age, gender, level of education, and employment status
using a conditional logistic regression. We also included
Lorant et al. BMC Psychiatry (2021) 21:112 Page 3 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
the social support score in order to control for the po-
tential bias affecting those with a lower level of social
support, who may have been more likely to participate
in the survey. We bootstrapped 1000 samples, stratified
on the three-way national distribution for age group,
gender, and level of education, and calculated a 95%
bootstrapped confidence interval using the percentile
method [37]. Aside from selection biases on observable
characteristics, such as gender, age, and education, het-
erogeneity of unobserved variables may also have af-
fected the measurements. In particular, people who felt
a sense of unease due to the COVID-19 pandemic or the
lockdown measures might be overrepresented in com-
parison with the general population, in an online survey.
In order to estimate the direction and magnitude of this
possible bias, we examined the effect of a well-known
risk factor for psychological distress that was available
both in our sample and in the BE.HIS2018 sample, i.e.
the score on the Oslo Social Support Scale. If our sample
was too sensitive to unobserved features, the odds ratio
would be greater (in absolute value) in our sample than
in the BE.HIS2018 sample. We therefore tested this hy-
pothesis by regressing the Oslo Social Support Scale on
psychological distress, controlling for the other socio-
demographic variables, and we compared the results of
the two samples. Steps 2 and 3 of the analysis were
weighted to match the European Standard Population.
All statistical analyses were performed using SAS 9.3 for
Linux.
Results
Sociodemographic characteristics and level of
psychological distress in the study sample
The sample is described in Table 1. More than half of
the respondents (52.9%) had experienced psychological
distress after less than a week of confinement on average
(5.6 days). Figure 1displays the proportion of respon-
dents who experienced psychological distress by age and
gender groups: black (for women) and grey (for men). In
all age groups, women were at greater risk of psycho-
logical distress than men. Psychological distress de-
creased linearly with age: younger females were almost
twice as likely to report psychological distress as older
females.
The risk factors of psychological distress are presented
in Table 2: Model 1 includes all the variables displayed
in the table, while Model 2 controls for age group, gen-
der, level of education, and the presence of a long-term
illness. Individuals who were exposed to COVID-19
were more likely to experience psychological distress
(Table 2). In Model 1, each additional point of exposure
to the illness was associated with a significant increase
in psychological distress (OR = 1.17, p< .001). A greater
decrease in social activity (OR = 1.11, p< .001), a higher
level of loneliness (OR = 1.45, p< .001), and a lower level
of social support (OR = 0.88, p< .001) were also associ-
ated with greater likelihood of psychological distress. A
change in occupational status was also associated with a
greater likelihood of psychological distress, including for
those who were teleworking more (OR = 1.35, p< .001).
Likewise, those who had experienced an increase in their
workload during lockdown were found to be at greater
risk of psychological distress than those who had not ex-
perienced workload changes (OR = 2.11, p< .001). The
results were similar in Model 2, in which confounders
were included. In general, the estimates remained signifi-
cant and of similar magnitude. The signs and the magni-
tude of the results were also similar to the continuous
score of psychological distress.
Comparison of the level of psychological distress with a
pre-COVID-19 study
Figure 2displays the differences between the
BE.HIS2018 samples (light grey) and the study samples
(dark grey) for each of the GHQ-12 items. Three items
stood out as showing a considerable increase: 57% of the
respondents in the study sample were less able to con-
centrate than usual (as against 14% in the BE.HIS2018
sample), 40% declared that they felt less useful than
usual (as against 11% in the BE.HIS2018 sample), and
62% felt constantly under strain (as against 29% in the
BE.HIS2018 sample).
Table 1 Descriptive statistics of the study sample, unweighted
March –April 2020
a
N= 20,792
% (or mean)
Age (mean, std) 43.6 (14.9)
Gender: 72.4
Women
Men 27.6
Education:
Secondary or lower 13.6
Higher 79.5
Other 6.9
Social support: 29.4
Weak
Moderate 47.8
Strong 22.8
Psychological distress: 47.1
No
Yes 52.9
GHQ –12 score (mean, std) 4.5 (3.5)
No. of days of confinement (mean, std) 5.6 (4.9)
a
COVID-19 pandemic study carried out in Belgium, March –April 2020
Lorant et al. BMC Psychiatry (2021) 21:112 Page 4 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
When comparing the rates of psychological distress in
the study and in the BE.HIS2018 samples, we observed
that the proportion of people who experienced psycho-
logical distress was much higher in the study sample
(52.8%) than in the BE.HIS2018 sample (18.3%). The
bootstrapped mean percentage of psychological distress
was 48.9% (95%BC: 48.3, 49.6). The unconditional ratio
of the study sample compared to the BE.HIS2018 sample
was 2.92, while the conditional rate ratio was 2.3
(95%CI: 2.16–2.45). Finally, we found that a higher level
of social support, as measured with the Oslo Social Sup-
port Scale, was associated with a lower risk of psycho-
logical distress in our sample (OR = 0.82, 95%CI: 0.81–
0.83), but with a smaller effect size than in the
BE.HIS2018 sample (OR = 0.75, 95%CI: 0.73–0.77), a dif-
ference that was statistically significant (p< 0.001).
Discussion
Main findings
From the first week of lockdown, half the respondents
displayed psychological distress, with women and young
people displaying the highest levels of psychological dis-
tress. A longer period of lockdown, a lower level of so-
cial support, a greater reduction in social activity,
changes in working conditions, and a higher level of ex-
posure to COVID-19 were all associated with greater
risk of psychological distress. Our study is original in
that it provides a comparison with a pre-COVID-19
study. That comparison suggests that the COVID-19
pandemic and subsequent confinement measures have
led to a more than twofold increase the level of psycho-
logical distress in the Belgian population compared to
normal levels, as measured in the Belgian Health Inter-
view Survey carried out in 2018.
Consistency with previous studies and interpretation of
findings
The level of psychological distress measured in our study
is quite similar to the results of recent studies carried
out in China [38,39], the USA [40], and other European
countries [41–45]. The difference in psychological dis-
tress before and after the lockdown is also similar to the
findings of a study in the UK which found that distress
increased from 19 to 27% [41] and to those of a study in
the USA which found that distress increased from 4 to
14% [40]. Another international study that compared
eight countries across four continents found that 30.2%
of the respondents displayed symptoms of generalised
Fig. 1 Level of psychological distress in the study sample (March –April 2020, during the COVID-19 lockdown period) by age and gender group:
percentage, weighted analysis
Lorant et al. BMC Psychiatry (2021) 21:112 Page 5 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
anxiety disorder or major depression [6]. Our findings
are also in line with those of Brooks and colleagues:
some studies included in that review showed a two- to
threefold increase in the psychological distress experi-
enced by those being quarantined, compared to the gen-
eral population. The finding that women were at greater
risk of psychological distress than men is also consistent
with previous studies [2,6,38,39]. The downward trend
according to age is an unsettled matter in the literature.
A greater risk of psychological distress among young
people was also reported in the international study men-
tioned above [6] and in a Chinese study [46]. This is
surprising, however, given that older age groups are at
greatest risk of mortality from COVID-19. Furthermore,
the use of social media, which younger people are gener-
ally believed to be more comfortable with, partially com-
pensates for social distancing. One possible explanation
for this finding is that confinement measures have a par-
ticularly strong (social, occupational, and psychological)
impact on younger people, particularly in the early days
of lockdown. Older people usually have limited social
capital and less diverse social and professional activities
than younger people and may, therefore, be less affected
by the confinement measures. This interpretation is
Table 2 Risk factors of categorical and continuous psychological distress: odds ratio and beta from the logistic and linear
regressions, weighted analysis
c
Psychological distress
Mean
(std)
or %
Categorical distress
a
Continuous score of distress
a
Model 1
b
Model 2
b
Model 1
b
Model 2
b
Covariates OR 95%CI p OR 95%CI p Beta 95%CI p Beta 95%CI p
Exposure to COVID-19 (no., 0 to 8) 0.94 (1.3) 1.17 1.14,
1.20
<.001 1.15 1.12,
1.18
<.001 0.17 0.14, 0.21 <.001 0.14 0.11, 0.17 <.001
Duration of lockdown (days, 1 to 21) 5.2 (4.9) 1.03 1.02,
1.04
<.001 1.03 1.02,
1.03
<.001 0.09 0.08, 0.10 <.001 0.09 0.08, 0.10 <.001
Decrease in social activity (score, −13
to 17)
3.8 (2.9) 1.11 1.10,
1.13
<.001 1.10 1.08,
1.11
<.001 0.16 0.14, 0.17 <.001 0.13 0.12, 0.15 <.001
Social support (score, 3 to 14) 9.1 (2.4) 0.88 0.87,
0.90
<.001 0.87 0.85,
0.88
<.001 −0.20 −0.22,-
0.18
<.001 −0.20 −0.22,-
0.18
<.001
Loneliness (score, 3 to 12) 6.1 (2.7) 1.45 1.42,
1.47
<.001 1.46 1.44,
1.49
<.001 0.65 0.63, 0.67 <.001 0.62 0.60, 0.64 <.001
Change in occupational status (ref = no change):
Lost job 1.3 5.24 3.57,
7.69
<.001 4.55 3.08,
6.71
<.001 1.53 1.20, 1.86 <.001 1.26 0.93, 1.58 <.001
Stopped working 14.0 1.08 0.95,
1.22
0.239 1.02 0.90,
1.16
0.775 0.41 0.26, 0.56 <.001 0.29 0.14, 0.45 <.001
More teleworking 47.7 1.35 1.23,
1.49
<.001 1.00 0.90,
1.11
0.950 0.58 0.46, 0.70 <.001 0.22 0.10, 0.35 <.001
More time in workplace 4.2 0.71 0.59,
0.87
<.001 0.54 0.44,
0.66
<.001 −0.42 −0.66,-
0.17
<.001 −0.73 −0.97,-
0.49
<.001
Other 14.2 1.24 1.11,
1.39
<.001 1.32 1.18,
1.49
<.001 0.51 0.37, 0.65 <.001 0.52 0.38, 0.66 <.001
Income (ref = no change):
Increase 0.5 0.43 0.26,
0.69
<.001 0.43 0.26,
0.71
<.001 −1.01 −1.49,-
0.53
<.001 −1.08 −1.55,-
0.61
<.001
Decrease 19.3 1.45 1.31,
1.60
<.001 1.48 1.34,
1.64
<.001 0.54 0.42, 0.67 <.001 0.53 0.41, 0.66 <.001
Workload (ref = no change):
Increase 21.3 2.11 1.90,
2.33
<.001 1.87 1.68,
2.08
<.001 0.85 0.72, 0.98 <.001 0.63 0.50, 0.76 <.001
Decrease 40.6 1.69 1.54,
1.85
<.001 1.43 1.30,
1.57
<.001 0.63 0.52, 0.74 <.001 0.37 0.26, 0.48 <.001
a
Categorical distress refers to GHQ12 > =4; continuous distress refers to the total score
b
Model 1 is controlled for all variables displayed in the table; Model 2 is additionally controlled for age group, gender, educational level, and presence of
long-term illness
c
Weighted according to a Standard European Population
Lorant et al. BMC Psychiatry (2021) 21:112 Page 6 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
supported by our analyses, which indicate that this age
trend vanished once changes in professional and social
activities were factored in.
The finding that greater risk of psychological distress
was associated with lockdown duration is consistent
with a study carried out in Toronto during the SARS
epidemic, which found that people who had spent longer
in quarantine were at greater risk of PTSD [11]. It is also
consistent with a study carried out in Flanders which
found that fear of loneliness was more widespread at the
beginning of the lockdown than later on [45]. We can-
not, however, dismiss the possibility of a selection bias
in our study: people who completed the survey later on
may have experienced more mental health issues or risk
factors than those who completed the survey earlier.
Further longitudinal studies would help to ascertain the
effect of the duration of lockdown. The role of health,
social, and occupational determinants of psychological
distress is consistent with a large body of research in so-
cial epidemiology [47–51]. The specific context of this
study, however, allows us to add to the literature the
finding that short-term changes in social activity, social
support, and working conditions resulting from suppres-
sion measures have an immediate effect on mental
health. One critical aspect is loneliness, which has a
major influence on psychological distress. This may sig-
nal the loss of a sense of belonging, a key mechanism in
the link between social capital, psychological health [47],
and physical health [52]. Detailed examination of the
GHQ-12 items indicated that there was a 29% increase
in the proportion of individuals who felt they were play-
ing a less useful role in life. This is a critical factor dur-
ing the COVID-19 pandemic. Being confined at home
and not being able to carry out personal and profes-
sional activities may strengthen that feeling, along
with perceived powerlessness to stem the pandemic
[53]. That sense of usefulness, therefore, could be tar-
geted by proper intervention. One possibility could be
to emphasise the role each individual can play in the
fight against the spread of COVID-19 and in taking
care of others [54].
Limitations
Despite the high number of responses received, the main
limitation of this study is a selection bias. The whole
population was invited to participate in an online survey
and those who responded, especially during the early
days of lockdown, were those who wanted to have a
voice. It is very likely, therefore, that the proportion of
people who felt a sense of unease due to the pandemic
and confinement measures was high among the respon-
dents. We have indicated that women, more highly edu-
cated people, and younger people were overrepresented
in the respondent sample; also, because of this sampling
selection, it is likely that we underestimated the propor-
tion of those with a more vulnerable occupational status.
Fig. 2 GHQ-12 items, percentages from the study sample (March –April 2020, during the COVID-19 lockdown period) and the BE.HIS2018
sample, weighted sample
Lorant et al. BMC Psychiatry (2021) 21:112 Page 7 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
The effects of this selection bias are, however, unclear.
The higher proportion of women makes it more likely
that the risk of psychological distress was overestimated,
as several studies have indicated that psychological dis-
tress is generally greater among women. Likewise, psy-
chological distress tended to be greater in younger age
groups in the Belgian Health Interview Survey than it
was reported to be in other studies [55], even if the pat-
tern whereby psychological distress decreases according
to age was less clear than in our study [30]. By contrast,
psychological distress was found to be greater among
less educated people than among more highly educated
people in the Belgian Health Interview Survey [30]. This
suggests that the proportion of highly educated people
in our sample may have led to an underestimation of
psychological distress. Furthermore, the use of an online
survey meant that we were unable to reach out to the
most vulnerable groups of the population, who had no
access to the survey. It is likely that the psychological
distress of the population was also underestimated for
that reason. It is difficult to separate the impacts of these
different factors. The bootstrapped average of psycho-
logical distress would indicate that the selection bias led
to an overestimation of the psychological distress in the
general population. The effect size of the odds ratio in
the study and the BE.HIS2018 samples, however, indi-
cates that the magnitude of risk factors was slightly
underestimated in our study.
Conclusions
The short-term health, social, and economic conditions
related to the COVID-19 pandemic and subsequent
lockdown measures were associated with a worsening of
the mental health of the general population in Belgium.
The effects were measurable from the very first days of
lockdown. The risk of psychological distress increased in
accordance with increases in exposure to COVID-19
and duration of confinement. This was one of the first
assessments of the mental health effects of the COVID-
19 pandemic and confinement measures in Europe to be
based on a large population sample. The findings indi-
cate that, from the point of view of mental health, the
authorities should limit the duration of lockdown and
social distancing measures to a minimum. The author-
ities should also pay attention to those groups of the
population that are most at risk of psychological distress,
e.g. women, young people, people who are experiencing
changes in their occupational status, and people who are
feeling lonely or socially isolated. There might be inter-
generational tension, as the mental health burden of
lockdown seems to fall most heavily on younger people,
even though the elderly are more at risk from COVID-
19. Mitigating the impact of lockdown on people’s social
and professional lives might be an effective strategy for
coping with long periods of lockdown. Further research
is needed, however, to evaluate whether the mental ef-
fects of COVID-19 and lockdown are sustained over lon-
ger periods. Likewise, further research should assess
whether these effects are similar, in nature and size, in
different countries, particularly by taking into account
differences in the intensity of the outbreak and the di-
versity of the suppression measures implemented in the
different countries affected.
Acknowledgements
This research was supported by a grant from the A.B. Fund managed by the
King Baudouin Foundation, grant number: 2020-J1812640-216406.
We thank Sciensano for the access to the BE.HIS2018 survey data.
We thank the two reviewers for their helpful comments and suggestions.
Authors’contributions
VL contributed to study conceptualisation and design, project administration,
funding acquisition, data acquisition, methodology, data analysis, manuscript
writing, and manuscript review. PS contributed to study conceptualisation
and design, data acquisition, methodology, data analysis, and manuscript
review. KVB contributed to project administration, data acquisition,
methodology, and manuscript review. PN contributed to study
conceptualisation and design, project administration, data acquisition,
methodology, manuscript writing, and manuscript review. The author(s) read
and approved the final manuscript.
Funding
This research was supported by a grant from the A.B. Fund managed by the
King Baudouin Foundation, grant #2020-J1812640–216406.
Availability of data and materials
Consent was obtained from the participants on condition that their data
would not be shared, as stipulated in the Data Management Plan. A limited
set of the data is included in the supporting information section of the
paper in order to allow analyses replication.
Ethics approval and consent to participate
Informed consent was obtained from all participants. Belgian law does not
require approval from an ethics committee for an online survey of the
general population. The study is, however, covered by privacy regulations.
Participants were provided with the legal information relating to consent. All
information related to respondents’consent and the GDPR is available on
request.
This is in accordance with applicable laws, including Regulation 2016/679 of
the European Parliament and of the Council adopted on 27 April 2016 on
the protection of natural persons with regard to the processing of personal
data and on the free movement of such data, and repealing Directive 95/46/
EC –the General Data Protection Regulation.
The study was carried out in full accordance with the relevant Belgian
guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The author(s) declare(s) that they have no competing interest.
Author details
1
Institute of Health and Society (IRSS), Université Catholique de Louvain,
Brussels, Belgium.
2
Family and Population Health (FAMPOP) & Collaborative
Antwerp Psychiatry Research Institute (CAPRI),Faculty of Medicine and Health
Sciences, University of Antwerp, Antwerp, Belgium.
Lorant et al. BMC Psychiatry (2021) 21:112 Page 8 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Received: 19 November 2020 Accepted: 8 February 2021
References
1. Tian H, Liu Y, Li Y, Wu C-H, Chen B, Kraemer MUG, et al. An investigation of
transmission control measures during the first 50 days of the COVID-19
epidemic in China. Science. 2020;368(6491):638–42. https://doi.org/10.1126/
science.abb6105.
2. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al.
The psychological impact of quarantine and how to reduce it: rapid review
of the evidence. Lancet. 2020;395(10227):912–20.
3. Jeong H, Yim HW, Song YJ, Ki M, Min JA, Cho J, et al. Mental health status
of people isolated due to Middle East respiratory syndrome. Epidemiol
Health. 2016;38:e2016048.
4. Qiu J, Shen B, Zhao M, Wang Z, Xie B, Xu Y. A nationwide survey of
psychological distress among Chinese people in the COVID-19 epidemic:
implications and policy recommendations. General Psychiatry. 2020;33(2):
e100213.
5. Bendau A, Petzold MB, Pyrkosch L, et al. Associations between COVID-19
related media consumption and symptoms of anxiety, depression and
COVID-19 related fear in the general population in Germany. Eur Arch
Psychiatry Clin Neurosci. 2020. https://doi.org/10.1007/s00406-020-01171-6.
6. Genereux M, Schluter PJ, Hung KK, Wong CS, Pui Yin Mok C, O'Sullivan T,
et al. One Virus, Four Continents, Eight Countries: An Interdisciplinary and
International Study on the Psychosocial Impacts of the COVID-19 Pandemic
among Adults. Int J Environ Res Public Health. 2020;17(22).
7. Kawachi I, Berkman LF. Social ties and mental health. J Urban Health. 2001;
78(3):458–67.
8. Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a
meta-analytic review. PLoS Med. 2010;7(7):e1000316.
9. Leigh-Hunt N, Bagguley D, Bash K, Turner V, Turnbull S, Valtorta N, et al. An
overview of systematic reviews on the public health consequences of social
isolation and loneliness. Public Health. 2017;152:157–71.
10. Rohde N, D’Ambrosio C, Tang KK, Rao P. Estimating the mental health
effects of social isolation. Appl Res Qual Life. 2016;11(3):853–69.
11. Hawryluck L, Gold WL, Robinson S, Pogorski S, Galea S, Styra R. SARS control
and psychological effects of quarantine, Toronto, Canada. Emerg Infect Dis.
2004;10(7):1206–12.
12. Liu X, Kakade M, Fuller CJ, Fan B, Fang Y, Kong J, et al. Depression after
exposure to stressful events: lessons learned from the severe acute
respiratory syndrome epidemic. Compr Psychiatry.
2012;53(1):15–23.
13. Wu P, Liu X, Fang Y, Fan B, Fuller CJ, Guan Z, et al. Alcohol abuse/
dependence symptoms among hospital employees exposed to a SARS
outbreak. Alcohol Alcohol. 2008;43(6):706–12.
14. Reynolds DL, Garay JR, Deamond SL, Moran MK, Gold W, Styra R.
Understanding, compliance and psychological impact of the SARS
quarantine experience. Epidemiol Infect. 2008;136(7):997–1007.
15. Palinkas LA, Johnson JC, Boster JS. Social support and depressed mood in
isolated and confined environments. Acta Astronautica. 2004;54(9):639–47.
16. Karasek R, Tr T. Healthy work : stress, productivity, and the reconstruction of
working life. New York: Basic Books; 1990. xiii. p. 381.
17. Woods M, Macklin R, Dawkins S, Martin A. Mental illness, social suffering and
structural antagonism in the labour process. Work Employ Soc. 2019;33(6):
948–65.
18. YaMei Bai MD, Chao-Cheng Lin MD, Chih-Yuan Lin MD, Jen-Yeu Chen MD,
Ching-Mo Chue MD, Pesus Chou PD. Survey of stress reactions among
health care workers involved with the SARS outbreak. Psychiatr Serv. 2004;
55(9):1055–7.
19. Han KM, Chang J, Won E, Lee MS, Ham BJ. Precarious employment
associated with depressive symptoms and suicidal ideation in adult wage
workers. J Affect Disord. 2017;218:201–9.
20. Wang G, Zhang Y, Zhao J, Zhang J, Jiang F. Mitigate the effects of home
confinement on children during the COVID-19 outbreak. Lancet. 2020;
395(10228):945–7.
21. Anyan F, Hjemdal O. Stress of home life and gender role socializations,
family cohesion, and symptoms of anxiety and depression. Women Health.
2018;58(5):548–64.
22. Wolff BC, Santiago CD, Wadsworth ME. Poverty and involuntary
engagement stress responses: examining the link to anxiety and aggression
within low-income families. Anxiety Stress Coping. 2009;22(3):309–25.
23. Mihashi M, Otsubo Y, Yinjuan X, Nagatomi K, Hoshiko M, Ishitake T.
Predictive factors of psychological disorder development during recovery
following SARS outbreak. Health Psychol. 2009;28(1):91–100.
24. Shor E, Roelfs DJ. Social contact frequency and all-cause mortality: a meta-
analysis and meta-regression. Soc Sci Med. 2015;128:76–86.
25. Smith KJ, Victor C. Typologies of loneliness, living alone and social isolation,
and their associations with physical and mental health. Ageing Soc. 2018;
39(8):1709–30.
26. Fiori KL, McIlvane JM, Brown EE, Antonucci TC. Social relations and depressive
symptomatology: self-efficacy as a mediator. Aging Ment Health. 2006;10(3):227–39.
27. Wang J, Mann F, Lloyd-Evans B, Ma R, Johnson S. Associations between
loneliness and perceived social support and outcomes of mental health
problems: a systematic review. BMC Psychiatry. 2018;18(1):156. https://doi.
org/10.1186/s12888-018-1736-5.
28. Molenberghs G, Faes C, Aerts J, Theeten H, Devleesschauwer B, Sierra NB,
et al. Belgian COVID-19 Mortality, Excess Deaths, Number of Deaths per
Million, and Infection Fatality Rates (8 March - 9 May 2020). medRxiv. 2020;
2020.06.20.20136234.
29. Demarest S, Berete F, Charafeddine R, Van der Heyden J. Enquête de santé
2018: Méthodologie. Brussels: Sciensano; 2019. 2019. Contract No.: D/2019/
14.440/25
30. Gisle L, Drieskens S, Demarest S, Van der Heyden J. Santé mentale. Enquête
de santé 2018. Brussels: Sciensano; 2020. 2020. Contract No.: D/2020/14.440/
3
31. Goldberg D, Williams P. GHQ : a user's guide to the general health
questionnaire. Bershire: Nfer-Nelson; 1988. p. 1–129.
32. Goldberg DP, Gater R, Sartorius N, Ustun TB, Piccinelli M, Gureje O, et al. The
validity of two versions of the GHQ in the WHO study of mental illness in
general health care. Psychol Med. 1997;27(1):191–7.
33. Hankins M. The reliability of the twelve-item general health questionnaire
(GHQ-12) under realistic assumptions. BMC Public Health. 2008;8(1):355.
34. Carnegie-Mellon-University. Social Participation: The Common Cold Project.
Pittsburgh: Carnegie Mellon University; 2016. Available from: https://www.
cmu.edu/common-cold-project/measures-by-study/psychological-and-socia
l-constructs/social-relationships-loneliness-measures/social-participation.html
35. Kocalevent RD, Berg L, Beutel ME, Hinz A, Zenger M, Harter M, et al. Social
support in the general population: standardization of the Oslo social
support scale (OSSS-3). BMC Psychol. 2018;6(1):31.
36. Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring
loneliness in large surveys: results from two population-based studies. Res
Aging. 2004;26(6):655–72.
37. Davison AC, Hinkley DV. Bootstrap methods and their application.
Cambridge: Cambridge University Press; 1997. p. 582.
38. Qiu J, Shen B, Zhao M, Wang Z, Xie B, Xu Y. A nationwide survey of
psychological distress among Chinese people in the COVID-19 epidemic:
Implications and policy recommendations. General Psychiatry. 2020;33(2).
39. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological
responses and associated factors during the initial stage of the 2019
coronavirus disease (COVID-19) epidemic among the general population in
China. Int J Environ Res Public Health. 2020;17(5).
40. McGinty EE, Presskreischer R, Han H, Barry CL. Psychological distress and
loneliness reported by US adults in 2018 and April 2020. JAMA.
2020;324(1):93–4.
41. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, et al. Mental health
before and during the COVID-19 pandemic: a longitudinal probability
sample survey of the UK population. Lancet Psychiatry. 2020;7(10):883–92.
42. Rossi R, Socci V, Talevi D, Mensi S, Niolu C, Pacitti F, et al. COVID-19
pandemic and lockdown measures impact on mental health among the
general population in Italy. Front Psychiatry. 2020;11:790.
43. White RG, Van Der Boor C. Impact of the COVID-19 pandemic and initial
period of lockdown on the mental health and well-being of adults in the
UK. BJPsych Open. 2020;6(5):e90.
44. Traunmuller C, Stefitz R, Gaisbachgrabner K, Schwerdtfeger A. Psychological
correlates of COVID-19 pandemic in the Austrian population. BMC Public
Health. 2020;20(1):1395.
45. De Coninck D, d'Haenens L, Matthijs K. Perceptions and opinions on the
COVID-19 pandemic in flanders, Belgium: data from a three-wave
longitudinal study. Data Brief. 2020;32:106060.
46. Ahmed MZ, Ahmed O, Aibao Z, Hanbin S, Siyu L, Ahmad A. Epidemic of
COVID-19 in China and associated psychological problems. Asian J
Psychiatr. 2020;51:102092. https://doi.org/10.1016/j.ajp.2020.102092.
Lorant et al. BMC Psychiatry (2021) 21:112 Page 9 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
47. Thoits PA. Mechanisms linking social ties and support to physical and
mental health. J Health Soc Behav. 2011;52(2):145–61.
48. Ehsan AM, De Silva MJ. Social capital and common mental disorder: a
systematic review. J Epidemiol Community Health. 2015;69(10):1021–8.
49. Cohen S. Social relationships and health. Am Psychol. 2004;59(8):676–84.
50. McKenzie K, Whitley R, Weich S. Social capital and mental health. Br J
Psychiatry. 2002;181(OCT):280–3.
51. De Silva MJ, McKenzie K, Harpham T, Huttly SRA. Social capital and mental
illness: a systematic review. J Epidemiol Community Health. 2005;59(8):619–
27.
52. Cole SW, Capitanio JP, Chun K, Arevalo JM, Ma J, Cacioppo JT. Myeloid
differentiation architecture of leukocyte transcriptome dynamics in
perceived social isolation. Proc Natl Acad Sci U S A. 2015;112(49):15142–7.
53. Mirowsky J, Ross C. Social causes of psychological distress. New York: Aldine
de Gruyter; 2003.
54. Taylor J, Turner RJ. A longitudinal study of the role and significance of
mattering to others for depressive symptoms. J Health Soc Behav. 2001;
42(3):310–25.
55. Larøi F, van der Linden M, DeFruyt F, van Os J, Aleman A. Associations
between delusion proneness and personality structure in non-clinical
participants: comparison between young and elderly samples.
Psychopathology. 2006;39(5):218–26.
Publisher’sNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Lorant et al. BMC Psychiatry (2021) 21:112 Page 10 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
Content uploaded by Pablo Nicaise
Author content
All content in this area was uploaded by Pablo Nicaise on Feb 19, 2021
Content may be subject to copyright.
